Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy.\u00a0Learn more<\/em><\/p>\n\n\n\n This dawning age of agentic AI requires a total rethink on how we build software. Current enterprise APIs were built for human use; the APIs of the future will be multi-model, native interfaces.\u00a0<\/p>\n\n\n\n \u201cWe need to build the kind of APIs that will work well with agents, because agents are the ones that are now going to interact with APIs, not humans,\u201d Merrin Kurien, principal engineer and AI platform architect at Intuit, said during the Women in AI breakfast at this year\u2019s VB Transform.\u00a0<\/p>\n\n\n\n Kurien had a dynamic discussion on the present and future of AI agents with fellow AI practitioners Mai-Lan Tomsen Bukovec, engineering and product leader for storage and compute services at AWS, and Tiffany To, SVP of product for platform and enterprise at Atlassian.<\/p>\n\n\n\n \u201cI would like to think five years from now, agents will be mainstream,\u201d said Kurien. \u201cA lot of the challenges we face today probably will be overcome with better tooling, if the last two-and-a-half years is any indication. How prepared will you be? It\u2019s dependent on your investments today.\u201d\u00a0<\/p>\n\n\n\n Intuit has been using agents and seeing \u201camazing progress,\u201d Kurien reported in the onstage panel, which was moderated by Betsy Peretti, partner for innovation and design at Bain.\u00a0<\/p>\n\n\n\n Notably, the financial technology platform company has incorporated automated invoice generation and reminders into its\u00a0QuickBooks\u00a0offering, which is popular among small and medium businesses (SMBs).<\/span>\u00a0<\/p>\n\n\n\n \u201cWe have seen businesses get paid on an average five days faster, and there\u2019s 10% more likelihood that invoices get paid in full,\u201d said Kurien.\u00a0<\/p>\n\n\n\n AWS has also seen success with\u00a0AWS Transform, an agile infrastructure that migrates .NET, mainframe, and VMware workloads into AWS, said Tomsen Bukovec.<\/span>\u00a0<\/p>\n\n\n\n The traditional migration scenario, as she described it: A customer would go to the application owner and request to, for instance, move their Windows application to a Linux-based application running on AWS. \u201cAnd guess what they would say? \u2018Take a number. You are priority number 42.’\u201d\u00a0<\/p>\n\n\n\n But now, enterprises can do the majority of those migrations with AI assistance. \u201cYour generalist teams are able to do way more work on their own, and it reduces the ask to the specialist,\u201d said Tomsen Bukovec. \u201cThat is changing migration as an industry.\u201d<\/p>\n\n\n\n Ultimately, how AWS and others evolve will be closely tied with how customers are using AI, she said. She marveled that incredible advancements in AI are \u201creally making us take a new look, a hot take\u201d on how to build applications.<\/p>\n\n\n\n \u201cWhen we build agentic infrastructures and we incorporate AI into the mission of our businesses, we\u2019re not just taking technology and putting it to work,\u201d said Tomsen Bukovec. \u201cWe are actually changing the nature of the workplace, the workforce.\u201d<\/p>\n\n\n\n She added, \u201cWe\u2019re seeing this happen right now. We\u2019re seeing this happen at warp speed.\u201d<\/p>\n\n\n\n Atlassian is taking a thoughtful inside-out approach to AI agents, said To.<\/p>\n\n\n\n For instance, the project management platform has launched an onboarding agent to help new employees access to all the materials they need to get started with their jobs. In the first month of launch, the agent fielded 7,000 requests. Now, it\u2019s just a regular part of the onboarding process, To said.\u00a0<\/p>\n\n\n\n Meanwhile, the company\u2019s go-to-market team has numerous interface points with customers, which can make it challenging to gather all the necessary context. Atlassian built a customer agent that pulls all that data together, and To reported that it is one of its most popular agents, used by 80 teams across the company. \u201cI use it quite a bit before I talk to customers,\u201d she acknowledged.\u00a0<\/p>\n\n\n\n At Atlassian, there is a strong responsibility to \u2018dog food\u2019 \u2014 using one\u2019s own products and services \u2014 and iteratively experiment to help guide customers as they evolve with AI, To explained. That work can then be translated into what Atlassian ships to customers out of the box.\u00a0<\/p>\n\n\n\n \u201cIt\u2019s not only going to come from engineering; it\u2019s going to come from across your entire organization,\u201d she said. \u201cSo what can you do programmatically to bring the creativity of everyone cross-functionally, to bring ideas together, to design workflows?\u201d<\/p>\n\n\n\n The company recently introduced its \u2018Teamwork Collection,\u2019 a curated selection of apps \u2014 Jira, Confluence and Loom \u2014 managed by \u2018rovo agents.\u2019 This is built into its platform and supports various aspects of the collaborative process. For instance, before a meeting, the agent will pull together a \u201creally nice summary\u201d based on Confluence pages and JIRA tickets.\u00a0<\/p>\n\n\n\n \u201cSo when you go into that meeting, you now have all that shared context,\u201d said To. \u201cYou\u2019re not trying to update each other, you can actually spend time on important strategy decisions.\u201d\u00a0<\/p>\n\n\n\n Atlassian estimates that that particular use case saves at least four hours per person per week. Customer HarperCollins, in particular, has used it to \u201cgreat effect,\u201d To noted. <\/p>\n\n\n\n Customers are using AI agents in varying complexities, she said: Sometimes they\u2019re just offloading work, gathering data or writing release notes; other times they\u2019re getting deep into raw data and pre-building strategic roadmaps.\u00a0<\/p>\n\n\n\n To explained that Atlassian has built a graph layer on top of its data that provides deeper intelligence on how data is connected. For instance, enterprises can analyze their goals alongside team structuring and projects in progress. \u201cIt\u2019s not just an HR org chart,\u201d said To.\u00a0<\/p>\n\n\n\n \u201cWhen you think about how people build their software development lifecycles right now, a huge part of that is creating roadmaps and prioritizing strategies,\u201d she said. \u201cBut that can be very dynamic, and taking into account all of that data is hard for humans to do. The agents we\u2019re seeing become really popular now with customers are actually pre-building those strategic roadmaps.\u201d<\/p>\n\n\n\n To emphasized the importance of creating feedback loops with customers, noting that, in just the last three months, Atlassian users have customized 10,000 different versions of the company\u2019s out-of-the-box agents.\u00a0<\/p>\n\n\n\n \u201cIt\u2019s a really great pool of feedback data that then helps us understand how they\u2019re embedding these agents into their workflows,\u201d said To. \u201cI think part of what is really exciting about this wave is it\u2019s such a collaborative process in designing with customers.\u201d<\/p>\n\n\n\n Trust is the cornerstone of any product and that should be no different with AI, Kurien emphasized. Customers want to know what the agent is doing behind the scenes and have control over its actions. This requires stringent review processes.\u00a0<\/p>\n\n\n\n \u201cWith new waves came new vulnerabilities,\u201d she said. \u201cWe have built a robust process where we are identifying the lifecycle in which an agent fits in and creating the right processes of reviews for that phase.\u201d\u00a0<\/p>\n\n\n\n To underscored the fact that it\u2019s more than raw technology; people must collaborate, build complete solutions together and tap into experience. The industry must invest in strong data architecture and have the right data context so that AI agents can make the powerful decisions we\u2019ll be asking of them.\u00a0<\/p>\n\n\n\n \u201cWhere it becomes really exciting is when it is a superpower in your organization, when it\u2019s able to help you make better decisions, release better products, re-sort your goals, be more competitive as a company,\u201d said To.\u00a0<\/p>\n\n\n\n She noted that there have been many waves of innovation over the years, but this one with AI is one all its own. \u201cI feel like with AI, it\u2019s a tidal wave. It\u2019s moment after moment after moment, right? AI is just completely different from all of the other waves.\u201d\u00a0<\/p> Editor\u2019s note: As a thank-you to our readers, we\u2019ve opened up early bird registration for VB Transform 2026 \u2014 just $200. This is where AI ambition meets operational reality, and you\u2019re going to want to be in the room. Reserve your spot now.\u00a0<\/em><\/p>\n Daily insights on business use cases with VB Daily<\/strong><\/p>\n If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.<\/p>\n \n\t\t\t\t\tThanks for subscribing. Check out more VB newsletters here.\n\t\t\t\t<\/p>\n An error occured.<\/p>\n<\/p><\/div>\n
\n<\/div>>>See all our Transform 2025 coverage here<<<\/strong>\n\n\nHow Intuit is getting invoices paid and AWS is supporting faster migration<\/h2>\n\n\n\n
How Atlassian is learning from experimentation internally and with customers\u00a0<\/h2>\n\n\n\n
Earning trust, building it right from the get-go<\/h2>\n\n\n\n
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